Active noise canceling is becoming increasingly popular in many audio environments wherein undesired sound is perceived by users. For example, headphones comprising active noise canceling functionality have become popular and are frequently used in many audio environments such as on noisy factory floors, in airplanes, and by people operating noisy equipment.
Active noise canceling headphones and similar systems are based on a microphone sensing the audio environment typically close to the users ear (e.g. within the acoustic volume created by the earphones around the ear). A noise cancellation signal is then radiated into the audio environment in order to reduce the resulting sound level. Specifically, the noise cancellation signal seeks to provide a signal with an opposite phase of the sound wave arriving at the microphone thereby resulting in a destructive interference that at least partly cancels out the noise in the audio environment. Typically, the active noise canceling system implements a feedback loop which generates the sound canceling signal based on the audio signal measured by the microphone in the presence of both the noise and the noise cancellation signal.
The performance of such noise cancellation loops is controlled by a feedback filter implemented as part of the feedback loop. The feedback filter is sought to be designed such that the optimum noise canceling effect can be achieved. Various algorithms and approaches for designing a feedback filter are known. For example, an approach for designing the feedback filter based on the Cepstral domain is described in J. Laroche. “Optimal Constraint-Based Loop-Shaping in the Cepstral Domain”, IEEE Signal process. letters, 14(4):225 to 227, April 2007.
However, as the feedback loop essentially represents an Infinite Impulse Response (IIR) filter, the design of the feedback filter is constrained by the requirement for the feedback loop to be stable. The stability of the overall closed loop filter is guaranteed by using Nyquist' stability theorem which requires that the overall closed loop transfer function does not encircle the point z=−1 in the complex plane for z=exp(jθ) with 0≦θ<2π.
However, whereas the feedback filter tends to be a fixed, non-adaptive filter in order to reduce complexity and simplify the design process, the transfer functions of parts of the feedback loop tend to vary substantially. Specifically, the feedback loop comprises a secondary path which represents other elements of the loop than the feedback filter including the response of the analog to digital and digital to analog converters, anti-aliasing filters, power amplifier, loudspeaker, microphone and the transfer function of the acoustic path from the loudspeaker to the error microphone. The transfer function of the secondary path varies substantially as a function of the current configuration of the headphones. For example, the transfer function of the secondary path may change substantially depending on whether the headphones are in a normal operational configuration (i.e. worn by a user), are not worn by a user, are pressed towards the head of a user etc.
Since the feedback loop has to be stable in all scenarios, the feedback filter is restricted by having to ensure stability for all different possible transfer functions of the secondary path. Therefore, the design of the feedback filter tends to be based on a worst case assumption for the transfer function of the secondary path. However, although such an approach may ensure stability of the system, it tends to result in reduced performance as the ideal noise canceling function for the specific current secondary path transfer function is not implemented by the feedback filter.
Hence, an improved noise canceling system would be advantageous and in particular a noise canceling system allowing increased flexibility, improved noise cancellation, reduced complexity, improved stability performance and characteristics, and/or improved performance would be advantageous.